CineIndexer
A movie database with AI-enabled search and a recommendation system to match user preferences.
About the Project :
CineIndexer is a comprehensive movie database platform that lets you search for world-famous movies by plot, specific scenes, or even vague details you remember. Can’t recall the title but know that one epic scene? Cineindexer’s got you covered!
My Role :
Full Stack Developer (MERN) | Self-initiated project
Tech Stack :
Key Features :
AI-powered movie search with natural language processing
Semantic search on world famouse movies
Personalized movie recommendations based on user preferences
Comprehensive movie database with detailed information
User authentication and profile management
Watchlist and rating system
Responsive design for mobile and desktop
Challenges Faced :
Performed data analysis to filter the most famous movies from the IMDb dataset (.tsv files)
One of the challenges was handling AI model rate limits, which I addressed through Cron job automation
Integrating multiple movie APIs and handling rate limits
Implementing efficient recommendation algorithms
Optimizing search performance with large datasets
Managing real-time data synchronization
Key Learnings :
Advanced API integration and error handling
Implemetation of vector database for Semantic search
Gained hands-on experience deploying applications on Railway, Render, and Vercel
AI/ML integration in web applications
Performance optimization for search functionality
User experience design for recommendation systems